Take a supercomputer. Give it wheels. The result: a robot that can take you anywhere you want to go. No wonder self-driving cars were the hot topic at CES last week, and the talk of the Detroit Auto Show this week.

Building this new generation of super-smart cars requires some serious intelligence. That’s why we introduced NVIDIA DRIVE PX 2, our artificial intelligence supercomputer for the car. We’re taking the GPU technology at the heart of a revolution that’s giving computers superhuman powers of perception and putting it in your driveway.

Here’s why your next car might be your first supercomputer:

AI Will Be Standard Equipment for Autonomous Vehicles

Only next generation AI has the adaptability, and the power, to understand what cars encounter on the road.

There aren’t enough engineers in Silicon Valley to hand-code software that can account for everything that happens when you drive. To deal with all the stuff a car sees on the road – and thanks to modern sensors, they see more and more – you need deep learning, a form of artificial intelligence. Last year, GPU-powered deep learning systems exceeded human levels of perception for the first time.

Our GPUs Make AI Practical

GPUs are built for parallel computing. So they’re ideal for deep neural networks – complex mathematical models that mimic the brain. DNNs are trained by feeding massive amounts of data into powerful computers. Parallel computing is the only practical way to digest this info rapidly. And DNNs are ideal for driving, because the more data you give them, the smarter they get.

NVIDIA DRIVE PX Brings AI to the Road

NVIDIA DRIVE PX 2 can perform 24 trillion deep learning operations per second, and it has the processing power of 150 MacBook Pros. It lets developers to replace the trunk full of GPU-based workstations in their vehicles with a supercomputer the size of a lunchbox.

We Built DRIVE PX to be a Scalable Platform for Car Companies

We designed DRIVE PX 2 to handle everything from advanced driver assistance systems to fully self-driving vehicles. It can be configured as a single-processor, air-cooled system for driver assistance, up to a four-processor, liquid-cooled system for autonomous driving. Whatever the case, it’s based on one scalable Architecture – the same that powers the world’s most advanced supercomputers.

DRIVE PX Is an Open Platform that any Self-Driving Car Maker Can Build Upon

NVIDIA DRIVE PX 2 is built with the same open, programmable GPU architecture that’s driving an AI revolution.

Audi, BMW, Ford, Mercedes and ZMP (makers of the RoboTaxi) are already using our AI platform for their autonomous car R&D. Our open, programmable platform is being used by More than 50 automakers, tier 1 suppliers, software companies and startups are using NVIDIA DRIVE PX to develop deep neural networks.

Car Companies Can Make Their Cars Safer Every Day

GPUs have already accelerated the training of deep neural networks by 20 to 30 times. What used to take months to train, now takes just days. This lets us create a brain for autonomous vehicles that is always alert, and can achieve superhuman levels of situational awareness. The more data these cars scoop up and share with one another, the smarter they all get.

AI-Equipped Cars Are Coming Soon

Earlier this month, Volvo announced it selected NVIDIA DRIVE PX 2 to power its fleet of autonomous cars. They’re outfitting their award-winning XC90 SUV with it – and will let drivers put these cars into autonomous driving mode on public roads around its hometown of Gothenburg, Sweden.

Everyone’s Investing in Automotive Supercomputing

GM has invested $500 million with Lyft on self-driving technologies. Toyota recently earmarked $1 billion for AI research. Just yesterday, the U.S. government put forth a $4 billion investment plan in support of autonomous driving technologies and the infrastructure to enable it.

This is just the start. Our goal is to make this technology available across all vehicle types and segments. Putting supercomputers on wheels is going to reduce the number accidents, injuries and fatalities. It’s going to make new capabilities – and new kinds of transportation – possible.